Trends and drivers of pharmaceutical expenditures from systemic anti-cancer therapy.

Expenditures on medicine for systemic anti-cancer therapy (SACT) have seen large increases in recent years. The characterization of patients with high SACT costs is crucial to identify cost-driving factors, but little is known about the distribution of expenditures at the patient-level. We priced 260,834 registrations of SACT for 12,589 patients from 2008 to 2019 by combining them with product-level billings of EUR 142.1 million. Based on this, we defined high-cost patients as the 2.5% most expensive by accumulated SACT expenditures. We found that high-cost patients accounted for 28.8% of the total SACT expenditures and were observed across all major cancer groups except for pancreatic cancer. The risk of becoming a high-cost patient was increased for younger age groups, i.e., 18-44 and 45-64 years, for patients with BMI ≥ 25, and for patients with multiple cancer diagnoses, while no alteration of risk was observed due to comorbidities or sex. Changes in the characteristics of high-cost patients during the study period were found with an increased risk of becoming high-cost in later years for elderly patients and patients with lung cancer and a decreased risk for breast cancer patients.

Dynamic Risk Prediction of 30-Day Mortality in Patients With Advanced Lung Cancer: Comparing Five Machine Learning Approaches.

PURPOSE: Administering systemic anticancer treatment (SACT) to patients near death can negatively affect their health-related quality of life. Late SACT administrations should be avoided in these cases. Machine learning techniques could be used to build decision support tools leveraging registry data for clinicians to limit late SACT administration. MATERIALS AND METHODS: Patients with advanced lung cancer who were treated at the Department of Oncology, Aalborg University Hospital and died between 2010 and 2019 were included (N = 2,368). Diagnoses, treatments, biochemical data, and histopathologic results were used to train predictive models of 30-day mortality using logistic regression with elastic net penalty, random forest, gradient tree boosting, multilayer perceptron, and long short-term memory network. The importance of the variables and the clinical utility of the models were evaluated. RESULTS: The random forest and gradient tree boosting models outperformed other models, whereas the artificial neural network-based models underperformed. Adding summary variables had a modest effect on performance with an increase in average precision from 0.500 to 0.505 and from 0.498 to 0.509 for the gradient tree boosting and random forest models, respectively. Biochemical results alone contained most of the information with a limited degradation of the performances when fitting models with only these variables. The utility analysis showed that by applying a simple threshold to the predicted risk of 30-day mortality, 40% of late SACT administrations could have been prevented at the cost of 2% of patients stopping their treatment 90 days before death. CONCLUSION: This study demonstrates the potential of a decision support tool to limit late SACT administration in patients with cancer. Further work is warranted to refine the model, build an easy-to-use prototype, and conduct a prospective validation study.

Immunophenotypically defined stem cell subsets in paediatric AML are highly heterogeneous and demonstrate differences in BCL-2 expression by cytogenetic subgroups.

In adult acute myeloid leukaemia (AML), immunophenotypic differences enable discrimination of leukaemic stem cells (LSCs) from healthy haematopoietic stem cells (HSCs). However, immunophenotypic stem cell characteristics are less explored in paediatric AML. Employing a 15-colour flow cytometry assay, we analysed the expression of eight aberrant surface markers together with BCL-2 on CD34+ CD38- bone marrow stem cells from 38 paediatric AML patients and seven non-leukaemic, age-matched controls. Furthermore, clonality was investigated by genetic analyses of sorted immunophenotypically abnormal stem cells from six patients. A total of 50 aberrant marker positive (non-HSC-like) subsets with 41 different immunophenotypic profiles were detected. CD123, CLEC12A, and IL1RAP were the most frequently expressed markers. IL1RAP, CD93, and CD25 expression were not restricted to stem cells harbouring leukaemia-associated mutations. Differential BCL-2 expression was found among defined cytogenetic subgroups. Interestingly, only immunophenotypically abnormal non-HSC-like subsets demonstrated BCL-2 overexpression. Collectively, we observed pronounced immunophenotypic heterogeneity within the stem cell compartment of paediatric AML patients. Additionally, certain aberrant markers used in adults seemed to be ineligible for detection of leukaemia-representing stem cells in paediatric patients implying that inference from adult studies must be done with caution.

Direct costs of antineoplastic and supportive treatment for progressive multiple myeloma in a tax-based health system.

Aim: To estimate current real-world costs of drugs and supportive care for the treatment of multiple myeloma in a tax-based health system. Methods: Forty-one patients were included from a personalized medicine study (2016-2019). Detailed information was collected from patient journals and hospital registries to estimate the total and mean costs using inverse probability weighting of censored data. Results: Total observed (censored) costs for the 41 patients was €8.84 million during 125 treatment years, with antineoplastic drugs as the main cost driver (€5.6 million). Individual costs showed large variations. Mean 3-year cost per patient from first progression was €182,103 (€131,800-232,405). Conclusion: Prediction of real-world costs is hindered by the availability of detailed costing data. Micro-costing analyses are needed for budgeting and real-world evaluation of cost-effectiveness.

Lay abstract In recent years, there has been a dramatic improvement in the treatment of multiple myeloma due to the introduction of new drugs. These drugs have significantly increased survival but have also had an immense impact on healthcare budgets. In this study, we used detailed treatment information for multiple myeloma patients in combination with billing data from the hospital pharmacy at a Danish hospital to calculate individual cost histories for both drugs and supportive care. Using these data, we estimated the mean 3-year cost of a multiple myeloma patient to be €182.103, but we also found large variation between patients, causing an uncertainty of €50.000 in either direction. We believe that detailed costing studies, similar to the present one, are necessary for evaluation of cost-effectiveness of drugs in clinical practice.

Development of a Precision Medicine Workflow in Hematological Cancers, Aalborg University Hospital, Denmark.

Within recent years, many precision cancer medicine initiatives have been developed. Most of these have focused on solid cancers, while the potential of precision medicine for patients with hematological malignancies, especially in the relapse situation, are less elucidated. Here, we present a demographic unbiased and observational prospective study at Aalborg University Hospital Denmark, referral site for 10% of the Danish population. We developed a hematological precision medicine workflow based on sequencing analysis of whole exome tumor DNA and RNA. All steps involved are outlined in detail, illustrating how the developed workflow can provide relevant molecular information to multidisciplinary teams. A group of 174 hematological patients with progressive disease or relapse was included in a non-interventional and population-based study, of which 92 patient samples were sequenced. Based on analysis of small nucleotide variants, copy number variants, and fusion transcripts, we found variants with potential and strong clinical relevance in 62% and 9.5% of the patients, respectively. The most frequently mutated genes in individual disease entities were in concordance with previous studies. We did not find tumor mutational burden or micro satellite instability to be informative in our hematologic patient cohort.